The Most Important Metric that Determines a Game’s Outcome

There are many metrics that fans use to describe a basketball game: points, field goal percentage (FGP), 3-pointer field goal percentage, free throw percentage, assists, steals, blocks, turnovers, rebounds, and many, many more.

My question is this: “What’s the most important metric that determines a basketball game’s outcome?”

Luckily for us, the answer is rather quite obvious. Every basketball game boils down to which team has scored more points. Therefore, the most telling metric is points scored. By comparing points scored by a team and its opponent, we can say which team has won with 100% certainty.

However, the question might not be so obvious if I asked about the second most important metric related to a game’s outcome. What are some other metrics that are associated with wins? Would it be the number of assists? Rebounds? Blocks? Steals? Maybe the field goal percentage?

I’ve set out to answer this question by analyzing regular season NBA games data since the 1995-1996 season.

For this study, I decided to look at the following metrics:

points scored

points scored from 2-pointers

points scored from 3-pointers

points scored from free throws

points scored from fast breaks

points scored “in paint”

steals

assists

blocks

defensive rebounds

offensive rebounds

rebounds

turnovers

fouls

estimated possessions

estimated offensive efficiency

field goals attempted (FGA)

field goals made (FGM)

field goal percentage (FGP)

2-pointer field goals attempted (2-pointer FGA)

2-pointer field goals made (2-pointer FGM)

2-pointer field goal percentage (2-pointer FGP)

3-pointer field goals attempted (3-pointer FGA)

3-pointer field goals made (3-pointer FGM)

3-pointer field goal percentage (3-pointer FGP)

free throws attempted

free throws made

free throw percentage

percentage of points scored from 2-pointers

percentage of points scored from 3-pointers

percentage of points scored from free throws

percentage of points scored from fast breaks

percentage of points scored “in paint”

For each metric, I obtained the metric’s values for two opposing teams. I then “retroactively predicted” each game’s outcome based on a simple comparison of the two values. Something like this: “If Team A recorded a higher Metric X than Team B, then predict that Team A has won the game,” where Metric X could be any of the metrics listed above.

I could then calculate the accuracy of these “retroactive predictions” using the following formula:

This “prediction accuracy” of a metric is a proxy for the metric’s association with winning, where a high accuracy suggests a strong association.

Not surprisingly, if we use points scored to make retroactive predictions on game outcomes, we’d predict teams who recorded higher points against their opponents would have won the games. And this yields 100% prediction accuracy, or 100% association rate. In other words, having a higher number of scored points is 100% associated winning games.

Using this method, I compiled the results of various metrics into the following table:

Metric

Accuracy

Number of Predictions

Points Scored

1.000

51972

Offensive Efficiency

0.964

51972

Field Goal Percentage (FGP)

0.797

51740

Field Goals Made (FGM)

0.782

48532

Defensive Rebounds

0.740

34196

Assists

0.727

48920

2-Pointer FGP

0.721

51676

3-Pointer FGP

0.670

50990

2-Pointer Points Scored

0.662

48886

2-Pointer FGM

0.662

48884

Rebounds

0.650

49790

3-Pointer Points Scored

0.624

46944

3-Pointer FGM

0.624

46944

Free Throws Made

0.624

49396

Blocks

0.615

45956

Points Scored “In Paint”

0.614

33868

Fouls Forced

0.608

48096

Free Throws Attempted

0.601

49832

Steals

0.599

46806

Fast-Break Points Scored

0.595

34396

Turnover Forced

0.589

47722

Free Throw Percentage

0.562

51328

% of Points from 3-Pointers

0.544

51930

% of Points from Fast Breaks

0.525

36224

% of Points from Free Throws

0.514

51938

3-Pointer FGA

0.501

49438

Offensive Rebounds

0.472

48174

2-Pointer FGA

0.464

50054

% of Points “In Paint”

0.460

36208

Field Goals Attempted (FGA)

0.459

49670

% of Points from 2-Pointers

0.441

51938

Estimated Possessions

0.430

51608

According to this table, the metric (other than points) that is most highly associated with winning is offensive efficiency, which measures how well a team converts a possession into points.

This was interesting because having a higher offensive efficiency was associated with wins 96.4% of the time, far more than having a higher field goal percentage, which was associated with wins 79.7% of the times.

In addition, while having more blocks, steals, and forced turnovers was positively associated with winning (61.5%, 59.9%, and 58.9%, respectively), having more defensive rebounds and assists showed profoundly stronger associations with wins (74% and 72.7%, respectively).

Moreover, as expected from my earlier blog post, having more offensive rebounds was more often associated with losses (52.8%) than with wins (47.2%).

Lastly, having a higher percentage of points scored via 2-point shots was more often associated with losses (55.9%) than with wins (44.1%). However, having a higher percentage of points scored via 3-point shots was more often associated with wins (54.4%) than with losses (45.6%). This is somewhat consistent with our finding from a previous blog post that teams that shoot more 3-pointers stand a better chance of scoring than those that don’t.

So how does this help us? This information is useful because it provides a method to focus on metrics that matter. When we have hundreds of metrics to look at, being able to focus on metrics that truly matter gives us an advantage.

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I’m a data practitioner by day, a web developer by night, a semi-competent swimmer, an active basketball player, a collector of cool ideas, an aspiring entrepreneur, a college dropout but a lifelong learner, and a self-professed nice guy. I love all things basketball, data, programming, and entrepreneurship.